{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T08:58:44Z","timestamp":1765357124952,"version":"3.37.3"},"reference-count":58,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61572376","U1811263","62032016","61972291"],"award-info":[{"award-number":["61572376","U1811263","62032016","61972291"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hong Kong Research Grants Council","award":["C1031-18 G"],"award-info":[{"award-number":["C1031-18 G"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2023,10,1]]},"DOI":"10.1109\/tkde.2022.3175536","type":"journal-article","created":{"date-parts":[[2022,5,19]],"date-time":"2022-05-19T20:30:42Z","timestamp":1652992242000},"page":"9864-9877","source":"Crossref","is-referenced-by-count":11,"title":["Intent Disentanglement and Feature Self-Supervision for Novel Recommendation"],"prefix":"10.1109","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4667-5794","authenticated-orcid":false,"given":"Tieyun","family":"Qian","sequence":"first","affiliation":[{"name":"School of Computer Science, Wuhan University, Hubei, China"}]},{"given":"Yile","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Computer Science, Wuhan University, Hubei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3370-471X","authenticated-orcid":false,"given":"Qing","family":"Li","sequence":"additional","affiliation":[{"name":"Hong Kong Polytechnic University, Hong Kong"}]},{"given":"Xuan","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Computer Science, Wuhan University, Hubei, China"}]},{"given":"Ke","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Computer Science, Wuhan University, Hubei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1062-0970","authenticated-orcid":false,"given":"Zhiyong","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer Science, Wuhan University, Hubei, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2011.15"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.14778\/2311906.2311916"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2012.119"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.2307\/41410406"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2018.00023"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2019.00057"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412222"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450086"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1080\/10696679.1999.11501836"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1108\/17505931011070578"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2792838.2800172"},{"key":"ref12","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Hamilton"},{"article-title":"Inductive matrix completion based on graph neural networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Zhang","key":"ref13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2891530"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2792838.2800183"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/592"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013830"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3038234"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052639"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9153"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080777"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331188"},{"key":"ref25","first-page":"6904","article-title":"A meta-learning perspective on cold-start recommendations for items","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Vartak"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331268"},{"key":"ref27","first-page":"4957","article-title":"Dropoutnet: Addressing cold start in recommender systems","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Volkovs"},{"article-title":"beta-VAE: Learning basic visual concepts with a constrained variational framework","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Higgins","key":"ref28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00955"},{"key":"ref30","first-page":"5712","article-title":"Learning disentangled representations for recommendation","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Ma"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412239"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.392"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401137"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403091"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449788"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.2307\/3149855"},{"article-title":"Self-Supervised Learning: Generative or Contrastive","year":"2020","author":"Liu","key":"ref37"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390294"},{"article-title":"Auto-encoding variational bayes","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kingma","key":"ref39"},{"article-title":"Variational graph auto-encoders","volume-title":"Proc. NeurIPS Workshop Bayesian Deep Learn.","author":"Kipf","key":"ref40"},{"key":"ref41","first-page":"14837","article-title":"Generating diverse high-fidelity images with VQ-VAE-2","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Razavi"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00674"},{"article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Radford","key":"ref43"},{"article-title":"Self-Supervised Graph Learning for Recommendation","year":"2020","author":"Wu","key":"ref44"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449844"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411954"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441783"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16578"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.22"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/2835776.2835837"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/521"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186070"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1145\/3373807"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.1986.10488093"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401233"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5329"},{"article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kingma","key":"ref57"},{"key":"ref58","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/10251471\/09778975.pdf?arnumber=9778975","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T22:42:07Z","timestamp":1705963327000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9778975\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,1]]},"references-count":58,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2022.3175536","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"type":"print","value":"1041-4347"},{"type":"electronic","value":"1558-2191"},{"type":"electronic","value":"2326-3865"}],"subject":[],"published":{"date-parts":[[2023,10,1]]}}}